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Field
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Theoretic algorithms of defense, and how those can/should be modified to account for human attacker’s biases. To accomplish this goal, we study attacker’s behavior and create cognitive computational models
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to implement and optimize AI/ML models for biomedical datasets. Preferred Knowledge, Skills and Abilities Mathematical Modeling: Strong foundation in numerical modeling, graph theory, and statistics. Algorithm
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ATAC sequencing, spatial transcriptomics, proteomics, whole-genome sequencing, functional screens, bioinformatics, and/or data algorithms including machine learning will be given preference. A successful
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may include but are not limited to: algorithm and software development; application or development of computational or statistical methods; data analysis; modeling; statistics and machine learning
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interest in methods development Experience in one or more of the following areas: algorithms development, transcriptome analysis, RNA modifications, statistics, machine learning, long read RNA-Sequencing
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Overview Eine Druckversion dieser Ausschreibung (PDF) steht Ihnen in den weiteren Registerkarten (z.B. „Bewerbungsvoraussetzungen“) zur Verfügung. A print version of this announcement (PDF) is available in the further tabs (e.g. “Application requirements”). Programme Description The Alfried...
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Responsibilities: Development of stochastic and analytical methods for nonlinear partial differential equations Implementation of relevant numerical experiments using deep learning algorithms Job Requirements: PhD
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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
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applicants for fellowships of six months or more on behalf of the Japan Society for the Promotion of Science (JSPS); the DAAD selects the fellows applying for shorter funding periods in the short-term
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and refine algorithms and models for large-scale language processing tasks, with a focus on healthcare data Contribute to developing new models, techniques and methods for clinical machine learning